"""
Hugging Face-test  Token: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

"""

from fastapi import FastAPI, File, UploadFile, HTTPException
from pydantic import BaseModel
from typing import Optional
import os
import logging
from transformers import pipeline
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
import time

app = FastAPI()

# 初始化问答模型
tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
model = AutoModelForQuestionAnswering.from_pretrained("bert-base-uncased")
qa_pipeline = pipeline("question-answering", model=model, tokenizer=tokenizer)

# 日志配置
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

@app.post("/upload/")
async def upload_pdf(file: UploadFile = File(...)):
    try:
        # 读取PDF文件内容
        content = await file.read()
        # 这里可以添加代码将PDF内容转换为文本
        # ...
        return {"message": "PDF uploaded successfully."}
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

@app.post("/summarize/")
async def summarize_pdf(file: UploadFile = File(...)):
    try:
        # 读取PDF文件内容
        content = await file.read()
        # 这里可以添加代码生成摘要
        # ...
        return {"summary": "Summary of the PDF content."}
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

@app.post("/ask/")
async def ask_question(question: str, file: UploadFile = File(...)):
    try:
        # 读取PDF文件内容
        content = await file.read()
        # 这里可以添加代码处理问题并返回答案
        # ...
        return {"answer": "Answer to the question."}
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

@app.get("/performance/")
def get_performance():
    # 这里可以添加代码返回性能指标
    # ...
    return {"performance": "Performance metrics."}

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=8000)